Robin Healy1, Ian C Kenny2, Andrew J Harrison2. 1. Department of Physical Education and Sport Sciences, University of Limerick, V94 T9PX, Ireland; Department of Sport and Health Sciences, Athlone Institute of Technology, N37 HD68, Ireland. Electronic address: rhealy@ait.ie. 2. Department of Physical Education and Sport Sciences, University of Limerick, V94 T9PX, Ireland; Health Research Institute, University of Limerick, Limerick, V94 T9PX, Ireland.
Abstract
PURPOSE: This study aimed to determine the accuracy of a 4 split time modelling method to generate velocity-time and velocity-distance variables in elite male 100-m sprinters and subsequently to assess the roles of key sprint parameters with respect to 100-m sprint performance. Additionally, this study aimed to assess the differences between faster and slower sprinters in key sprint variables that have not been assessed in previous work. METHODS: Velocity-time and velocity-distance curves were generated using a mono-exponential function from 4 split times for 82 male sprinters during major athletics competitions. Key race variables-maximum velocity, the acceleration time constant (τ), and percentage of velocity lost (vLoss)-were derived for each athlete. Athletes were divided into tertiles, based on 100-m time, with the first and third tertiles considered to be the faster and slower groups, respectively, to facilitate further analysis. RESULTS: Modelled split times and velocities displayed excellent accuracy and close agreement with raw measures (range of mean bias was -0.2% to 0.2%, and range of intraclass correlation coefficients (ICCs) was 0.935 to 0.999) except for 10-m time (mean bias was 1.6% ± 1.3%, and the ICC was 0.600). The 100-m sprint performance time and all 20-m split times had a significant near-perfect negative correlation with maximum velocity (r ≥ -0.90) except for the 0 to 20-m split time, where a significantly large negative correlation was found (r = -0.57). The faster group had a significantly higher maximum velocity and τ (p < 0.001), and no significant difference was found for vLoss (p = 0.085). CONCLUSION: Coaches and researchers are encouraged to utilize the 4 split time method proposed in the current study to assess several key race variables that describe a sprinter's performance capacities, which can be subsequently used to further inform training.
PURPOSE: This study aimed to determine the accuracy of a 4 split time modelling method to generate velocity-time and velocity-distance variables in elite male 100-m sprinters and subsequently to assess the roles of key sprint parameters with respect to 100-m sprint performance. Additionally, this study aimed to assess the differences between faster and slower sprinters in key sprint variables that have not been assessed in previous work. METHODS: Velocity-time and velocity-distance curves were generated using a mono-exponential function from 4 split times for 82 male sprinters during major athletics competitions. Key race variables-maximum velocity, the acceleration time constant (τ), and percentage of velocity lost (vLoss)-were derived for each athlete. Athletes were divided into tertiles, based on 100-m time, with the first and third tertiles considered to be the faster and slower groups, respectively, to facilitate further analysis. RESULTS: Modelled split times and velocities displayed excellent accuracy and close agreement with raw measures (range of mean bias was -0.2% to 0.2%, and range of intraclass correlation coefficients (ICCs) was 0.935 to 0.999) except for 10-m time (mean bias was 1.6% ± 1.3%, and the ICC was 0.600). The 100-m sprint performance time and all 20-m split times had a significant near-perfect negative correlation with maximum velocity (r ≥ -0.90) except for the 0 to 20-m split time, where a significantly large negative correlation was found (r = -0.57). The faster group had a significantly higher maximum velocity and τ (p < 0.001), and no significant difference was found for vLoss (p = 0.085). CONCLUSION: Coaches and researchers are encouraged to utilize the 4 split time method proposed in the current study to assess several key race variables that describe a sprinter's performance capacities, which can be subsequently used to further inform training.
Authors: Jean-Benoît Morin; George Petrakos; Pedro Jiménez-Reyes; Scott R Brown; Pierre Samozino; Matt R Cross Journal: Int J Sports Physiol Perform Date: 2016-11-11 Impact factor: 4.010